machine learning algorithm

Control and Estimation Designs Using Model-Based and Model-Free Approaches for Water Quality Monitoring in Process Systems

Fahad Aljehani, Ph.D. Student, Electrical and Computer Engineering

Apr 30, 10:00 - 12:00

B1 L4 R4214

machine learning algorithm optimal control Control Theory Reinforcement Learning

This dissertation develops and evaluates advanced control and estimation strategies to address complex dynamics and measurement limitations in water-related applications, specifically optimizing fish growth in aquaculture and estimating bacterial concentration in wastewater treatment plants.

Fahad Aljehani

Ph.D. Student, Electrical and Computer Engineering

Control Theory optimal control Reinforcement Learning machine learning algorithm

Designing advanced control algorithms and estimation techniques to optimize water quality systems, specifically aquaculture and wastewater treatment, blending control theory with cutting-edge AI and machine learning to enhance performance, sustainability, and cost-efficiency.

Helping computers to see who we really are

1 min read · Sat, Oct 8 2016

algorithm machine learning algorithm

Algorithms that train computers to automatically detect human activity in videos can improve online searches and real-world surveillance systems.

Yasmine Marani

Ph.D. Student, Electrical and Computer Engineering

Aerial Robotics Dynamical Systems Controller design machine learning algorithm Estimation Control Theory

Yasmine is a Ph.D. candidate in Electrical and Computer Engineering under the supervision of Prof. Eric Feron and Prof. Meriem Laleg. She specializes in control theory, robotics, and artificial intelligence. Her research focuses on estimation problems for complex nonlinear systems with application to unmanned aerial vehicles (UAV) in uncertain environments.